Evaluation of a neuro‐fuzzy technique in estimating pan evaporation values in low‐altitude locations

[1]  J. Griffiths.  Another evaporation formula , 1966 .

[2]  Ozgur Kisi,et al.  Evapotranspiration estimation using feed-forward neural networks , 2006 .

[3]  Ö. Kisi.  Generalized regression neural networks for evapotranspiration modelling , 2006 .

[4]  Pau Martí,et al.  Assessment of a 4-input artificial neural network for ETo estimation through data set scanning procedures , 2010, Irrigation Science.

[5]  Ozgur Kisi,et al.  Predicting daily pan evaporation by soft computing models with limited climatic data , 2015 .

[6]  Pute Wu,et al.  GANN models for reference evapotranspiration estimation developed with weather data from different climatic regions , 2014, Theoretical and Applied Climatology.

[7]  de Bruin,et al.  A Simple Model for Shallow Lake Evaporation , 1978 .

[8]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[9]  Ozgur Kisi,et al.  Generalized Neurofuzzy Models for Estimating Daily Pan Evaporation Values from Weather Data , 2012 .

[10]  Edward T. Linacre,et al.  Climate and the Evaporation from Crops , 1967 .

[11]  Pau Martí,et al.  Ancillary data supply strategies for improvement of temperature-based ETo ANN models , 2010 .

[12]  T.,et al.  Training Feedforward Networks with the Marquardt Algorithm , 2004 .

[13]  Özgür Kisi,et al.  Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations , 2011, Comput. Geosci..

[14]  Ozgur Kisi,et al.  Estimating daily reference evapotranspiration using available and estimated climatic data by adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) , 2013 .

[15]  Mohammad Ali Ghorbani,et al.  Estimating daily pan evaporation from climatic data of the State of Illinois, USA using adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) , 2011 .

[16]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[17]  Ozgur Kisi,et al.  Comparison of heuristic and empirical approaches for estimating reference evapotranspiration from limited inputs in Iran , 2014 .

[18]  C. Priestley,et al.  On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters , 1972 .

[19]  Narendra Singh Raghuwanshi,et al.  Development and Validation of GANN Model for Evapotranspiration Estimation , 2009 .

[20]  Ali Aytek,et al.  Co-active neurofuzzy inference system for evapotranspiration modeling , 2009, Soft Comput..

[21]  M. Keskin,et al.  Fuzzy logic model approaches to daily pan evaporation estimation in western Turkey / Estimation de l’évaporation journalière du bac dans l’Ouest de la Turquie par des modèles à base de logique floue , 2004 .

[22]  Robert D. Burman.  Intercontinental Comparison of Evaporation Estimates , 1976 .

[23]  W. Brutsaert.  Evaporation into the atmosphere , 1982 .

[24]  Vijay P. Singh,et al.  Evaluation of gene expression programming approaches for estimating daily evaporation through spatial and temporal data scanning , 2014 .

[25]  Ozgur Kisi,et al.  Adaptive Neurofuzzy Computing Technique for Evapotranspiration Estimation , 2007 .

[26]  T. A. Costello,et al.  Estimating pan evaporation using limited meteorological observations , 1991 .

[27]  J. Wallace,et al.  Calculating evaporation: resistance to factors , 1995 .

[28]  O. Kisi,et al.  Application of Artificial Intelligence to Estimate Daily Pan Evaporation Using Available and Estimated Climatic Data in the Khozestan Province (South Western Iran) , 2011 .

[29]  Ozgur Kisi,et al.  Daily pan evaporation modelling using a neuro-fuzzy computing technique , 2006 .

[30]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..